Accurate detection of analytes in solutions, particularly biological fluids, is critical in several fields, including medical diagnostics, veterinary diagnostics, and food and drug safety. The innate turbidity of complex biological samples, such as blood, plasma, serum, urine, and bile, has made it difficult to develop reliable assays and devices for multiple analytes. Matrix-related interference as well as scattering of light by biocolloids hamper sensitive determinations of analytes where measurements are primarily restricted to turbidity.
Various types of qualitative and quantitative detection assays have been developed for several analytes based on the phenomena of surface plasmon resonance (SPR) and localized surface plasmon resonance (LSPR). SPR occurs in metallic surfaces when surface plasmons are excited. The phenomenon is characterized by a graded reduction in the intensity of the reflected light due to the molecular thickness of the metal surfaces when incident light strikes the surface at a certain angle. LSPR is a similar phenomenon observed in mono-dispersed metallic nanoparticles. The collective oscillations of the surface plasmons result in wavelength selective absorption and scattering of the incident radiation.
Binding of substances, like macromolecules, to the metallic surface or to binding partners absorbed onto the metallic surface can be detected by changes in the local refractive index manifested as shifts in the absorbance spectra. Such assays are incredibly sensitive due to the nature of the interaction of the surface plasmons and the boundary between the metallic surface and the neighboring medium (e.g. air or water). The drawback of using LSPR for detecting a specific analyte in biological samples has always been interference due to non-specific reaction. The opportunity for non-specific interactions in biological samples is particularly high because of macromolecules present in the sample matrix. Such non-specific interactions can result in an incorrect estimation of the concentration of analyte and even false positives. Therefore, it would be desirable to develop methods for reducing or eliminating non-specific interactions from components in sample matrices, especially biological sample matrices, in detection assays based on SPR or LSPR.